Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

Teresa Reguly, Ashton Breitkreutz, Lorrie Boucher, Bobby Joe Breitkreutz, Gary C. Hon, Chad L. Myers, Ainslie Parsons, Helena Friesen, Rose Oughtred, Amy Tong, Chris Stark, Yuen Ho, David Botstein, Brenda Andrews, Charles Boone, Olga G. Troyanskya, Trey Ideker, Kara Dolinski, Nizar N. Batada, Mike Tyers

Research output: Contribution to journalArticle

255 Citations (Scopus)

Abstract

Background. The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results. We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. Conclusion. Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.

Original languageEnglish (US)
Article number11
JournalJournal of Biology
Volume5
DOIs
StatePublished - Dec 1 2006

Fingerprint

Yeast
Saccharomyces cerevisiae
Throughput
Proteins
proteins
Genes
prediction
Essential Genes
Complex networks
Electric network analysis
Genetic Databases
Literature
Benchmarking
Protein Databases
Saccharomycetales
Datasets
Gene Regulatory Networks
yeasts
Publications
Databases

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Reguly, T., Breitkreutz, A., Boucher, L., Breitkreutz, B. J., Hon, G. C., Myers, C. L., ... Tyers, M. (2006). Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae. Journal of Biology, 5, [11]. https://doi.org/10.1186/jbiol36

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae. / Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby Joe; Hon, Gary C.; Myers, Chad L.; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G.; Ideker, Trey; Dolinski, Kara; Batada, Nizar N.; Tyers, Mike.

In: Journal of Biology, Vol. 5, 11, 01.12.2006.

Research output: Contribution to journalArticle

Reguly, T, Breitkreutz, A, Boucher, L, Breitkreutz, BJ, Hon, GC, Myers, CL, Parsons, A, Friesen, H, Oughtred, R, Tong, A, Stark, C, Ho, Y, Botstein, D, Andrews, B, Boone, C, Troyanskya, OG, Ideker, T, Dolinski, K, Batada, NN & Tyers, M 2006, 'Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae', Journal of Biology, vol. 5, 11. https://doi.org/10.1186/jbiol36
Reguly, Teresa ; Breitkreutz, Ashton ; Boucher, Lorrie ; Breitkreutz, Bobby Joe ; Hon, Gary C. ; Myers, Chad L. ; Parsons, Ainslie ; Friesen, Helena ; Oughtred, Rose ; Tong, Amy ; Stark, Chris ; Ho, Yuen ; Botstein, David ; Andrews, Brenda ; Boone, Charles ; Troyanskya, Olga G. ; Ideker, Trey ; Dolinski, Kara ; Batada, Nizar N. ; Tyers, Mike. / Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae. In: Journal of Biology. 2006 ; Vol. 5.
@article{f1f175809de54a87bb250e81245442af,
title = "Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae",
abstract = "Background. The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results. We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14{\%} coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. Conclusion. Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.",
author = "Teresa Reguly and Ashton Breitkreutz and Lorrie Boucher and Breitkreutz, {Bobby Joe} and Hon, {Gary C.} and Myers, {Chad L.} and Ainslie Parsons and Helena Friesen and Rose Oughtred and Amy Tong and Chris Stark and Yuen Ho and David Botstein and Brenda Andrews and Charles Boone and Troyanskya, {Olga G.} and Trey Ideker and Kara Dolinski and Batada, {Nizar N.} and Mike Tyers",
year = "2006",
month = "12",
day = "1",
doi = "10.1186/jbiol36",
language = "English (US)",
volume = "5",
journal = "Journal of Biology",
issn = "1478-5854",
publisher = "BioMed Central Ltd.",

}

TY - JOUR

T1 - Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

AU - Reguly, Teresa

AU - Breitkreutz, Ashton

AU - Boucher, Lorrie

AU - Breitkreutz, Bobby Joe

AU - Hon, Gary C.

AU - Myers, Chad L.

AU - Parsons, Ainslie

AU - Friesen, Helena

AU - Oughtred, Rose

AU - Tong, Amy

AU - Stark, Chris

AU - Ho, Yuen

AU - Botstein, David

AU - Andrews, Brenda

AU - Boone, Charles

AU - Troyanskya, Olga G.

AU - Ideker, Trey

AU - Dolinski, Kara

AU - Batada, Nizar N.

AU - Tyers, Mike

PY - 2006/12/1

Y1 - 2006/12/1

N2 - Background. The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results. We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. Conclusion. Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.

AB - Background. The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results. We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. Conclusion. Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.

UR - http://www.scopus.com/inward/record.url?scp=33847064282&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33847064282&partnerID=8YFLogxK

U2 - 10.1186/jbiol36

DO - 10.1186/jbiol36

M3 - Article

C2 - 16762047

AN - SCOPUS:33847064282

VL - 5

JO - Journal of Biology

JF - Journal of Biology

SN - 1478-5854

M1 - 11

ER -